How Data Analytics Can Benefit Smart Metering

The deployment of smart meters is creating great pressure on the electricity industry. The industry is looking to data analysis tools which will help to analyse transactional data in order to provide much needed solutions.
Published: Tue 28 Jan 2014

The UK is a complex energy market, supported by a centralised data transfer infrastructure which is cost-effective and secure. However, as smart meter deployments grow, this system will come under immense pressure.

The UK’s Department of Energy and Climate Change intends to roll out four million smart meters across the country by 2014. With this level of deployment, a number of issues will arise. This is where data analytics will be able to provide some transparency and efficiency to the processes carried out between market participants.

Stuart Lacey, Chief Executive, ElectraLink, discusses how data analytics can benefit the smart metering process and help resolve various market challenges :

No visibility of smart meter installations

Installation events can be aggregated to give suppliers a more detailed view of installations across an entire region. The information can then be made more granular in order to obtain more detailed information on specific regions, suburbs, and industry sectors. By overlaying third party data, standard industry codes provide very useful data. Every installation event can be tracked in this way.

Mr Lacey says that data analytic companies need to understand the meter supplier’s or utility’s requirements in order to provide them with the data required.

Mr Lacey points out that visibility of the progress of deployments will help the industry see what’s going on. They can then focus their investment more wisely and ensure a more efficient and low-risk deployment process.

Benchmarking marketing performance

There is a huge data gap when it comes to marketing processes. Through efficient customer engagement, supplies and marketing can be greatly improved.

“Customer regains” is a key marketing metric in the UK market as it measures how many customers return to a supplier after having left them. Mr Lacey says that this tool is used to measure how effective a supplier’s marketing is. This can be done by using postcodes. Regain performances can also be benchmarked against the entire industry.

Says Mr Lacey, “Customer insight data is key to understanding their business, and suppliers are showing a great deal of interest in this.”

Solve on-going issues with end to end market processes

Data flows are fragmented and not everyone sees the end-to-end data flow. To resolve this, a meter point administration number (meter registration number) and supplier data can be used as key fields to capture all the data that makes up a single change of supplier event, for instance. By doing this, the industry will have real insight into the reasons for supplier changes.

Reducing risk of stranded assets

A change of supplier increases the risk of assets disappearing. Data analytics will be able to track the meters as they move from supplier to supplier.

The gas industry has a huge problem with the transferring of assets between customers and the change of supply process. For this reason, many in the gas industry have adopted the Notification of Old Supply Information (NOSI) system.

With the use of this data, meter asset providers can track their assets in the gas market. In this way, the market will become more efficient. They will also then be able to offer cheaper prices to suppliers for their services because of the low risk of assets.

Continue to drive down distribution losses

Incorrect profiles for non half hourly sites (NHH), failed registrations, unregistered sites, erroneous energisation status, erroneously large consumption, negative consumption (consumption should be reported as a positive value), are all to blame for non-technical losses.

Through the use of data analytics, non technical losses (caused mainly by poor quality data) will be reduced.

There is great potential within the field of smart meter analytics. As analytical techniques develop to support the deployment of smart meters, the whole electricity industry and its customers are bound to benefit from this new rich stream of data.